Detecting bends and fabric folds using stitched sensors

Guido Gioberto, James P. Coughlin, K. Bibeau, Lucy E. Dunne
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引用次数: 37

Abstract

In this paper we describe a novel method for detecting bends and folds in fabric structures. Bending and folding can be used to detect human joint angles directly, or to detect possible errors in the signals of other joint-movement sensors due to fabric folding. Detection is achieved through measuring changes in the resistance of a complex stitch, formed by an industrial coverstitch machine using an un-insulated conductive yarn, on the surface of the fabric. We evaluate self-intersecting folds which cause short-circuits in the sensor, creating a quasi-binary resistance response, and non-contact bends, which deform the stitch structure and result in a more linear response. Folds and bends created by human movement were measured on the dorsal and lateral knee of both a robotic mannequin and a human. Preliminary results are promising. Both dorsal and lateral stitches showed repeatable characteristics during testing on a mechanical mannequin and a human.
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使用缝式传感器检测弯曲和织物褶皱
本文描述了一种检测织物结构弯曲和褶皱的新方法。弯曲和折叠可用于直接检测人体关节角度,或检测由于织物折叠而导致的其他关节运动传感器信号可能出现的误差。检测是通过测量复杂针脚的电阻变化来实现的,这种复杂针脚是由工业复缝机使用非绝缘导电纱在织物表面形成的。我们评估了自相交折叠,它会导致传感器短路,产生准二元电阻响应,以及非接触弯曲,它会变形针脚结构,导致更线性的响应。研究人员测量了人体机器人模型和人的膝盖背部和外侧的褶皱和弯曲。初步结果令人鼓舞。在机械模型和人体的测试中,背部和侧面缝合都显示出可重复的特征。
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The Semantic Web: 19th International Conference, ESWC 2022, Hersonissos, Crete, Greece, May 29 – June 2, 2022, Proceedings Correction to: A Semantic Framework to Support AI System Accountability and Audit The Semantic Web: 18th International Conference, ESWC 2021, Virtual Event, June 6–10, 2021, Proceedings QAnswer KG: Designing a Portable Question Answering System over RDF Data Incremental Multi-source Entity Resolution for Knowledge Graph Completion
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